Actuator and sensor faults estimation based on proportional integral observer for TS fuzzy model

This paper presents a novel method to address a Proportional Integral observer design for the actuator and sensor faults estimation based on Takagi–Sugeno fuzzy model with unmeasurable premise variables. The faults are assumed as time-varying signals whose kth time derivatives are bounded. Using Lya...

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Bibliographic Details
Published inJournal of the Franklin Institute Vol. 354; no. 6; pp. 2524 - 2542
Main Authors Youssef, T., Chadli, M., Karimi, H.R., Wang, R.
Format Journal Article
LanguageEnglish
Published Elmsford Elsevier Ltd 01.04.2017
Elsevier Science Ltd
Subjects
Analysis
Computer simulation
Fault diagnosis
Faults
Fuzzy sets
Linear matrix inequalities
Matrix methods
Proportional integral
Stability analysis
Variables
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Summary:This paper presents a novel method to address a Proportional Integral observer design for the actuator and sensor faults estimation based on Takagi–Sugeno fuzzy model with unmeasurable premise variables. The faults are assumed as time-varying signals whose kth time derivatives are bounded. Using Lyapunov stability theory and L2 performance analysis, sufficient design conditions are developed for simultaneous estimation of states and time-varying actuator and sensor faults. The Proportional Integral observer gains are computed by solving the proposed conditions under Linear Matrix Inequalities constraints. A simulation example is provided to illustrate the effectiveness of the proposed approach.
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content type line 14
ISSN:0016-0032
1879-2693
0016-0032
DOI:10.1016/j.jfranklin.2016.09.020